Investigating the Ulansuhai Lake in southwest Inner Mongolia, China, this study uses a holistic approach that incorporates many datasets and approaches to evaluate the ecological environmental quality of the area. The...
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Energy efficiency has emerged as a critical concern in Wireless Sensor Networks (WSN). Sensor nodes deplete their energy faster and die earlier making whole network unstable due to poor clustering in the network. Ther...
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Currently,e-learning is one of the most prevalent educational methods because of its need in today’s *** classrooms and web-based learning are becoming the new method of teaching *** students experience a lack of acc...
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Currently,e-learning is one of the most prevalent educational methods because of its need in today’s *** classrooms and web-based learning are becoming the new method of teaching *** students experience a lack of access to resources commonly the educational *** remote loca-tions,educational institutions face significant challenges in accessing various web-based materials due to bandwidth and network infrastructure *** objective of this study is to demonstrate an optimization and queueing tech-nique for allocating optimal servers and slots for users to access cloud-based e-learning *** proposed method provides the optimization and queue-ing algorithm for multi-server and multi-city constraints and considers where to locate the best *** optimal server selection,the Rider Optimization Algo-rithm(ROA)is utilized.A performance analysis based on time,memory and delay was carried out for the proposed methodology in comparison with the exist-ing *** proposed Rider Optimization Algorithm is compared to Par-ticle Swarm Optimization(PSO),Genetic Algorithm(GA)and Firefly Algorithm(FFA),the proposed method is more suitable and effective because the other three algorithms drop in local optima and are only suitable for small numbers of user *** the proposed method outweighs the conventional techniques by its enhanced performance over them.
In the last decade, due to the widespread and inexpensive availability of digital video cameras, digital videos (DV) are employed for security purposes daily, and they are generally regarded as a more credible form of...
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In the last decade, due to the widespread and inexpensive availability of digital video cameras, digital videos (DV) are employed for security purposes daily, and they are generally regarded as a more credible form of evidence than still photographs. Due to the tremendous growth of video editing tools, anyone with access to advanced editing software and a modern Smartphone can easily do digital video manipulations and fake it. As a result, to utilize video content as proof in court, it is necessary to evaluate and determine whether it is original or modified. To check the integrity and validity of video recordings, digital forgery detection techniques are required. The objective of the study is to present a systematic review of techniques for detecting forgery in digital videos. We conducted a systematic literature review (SLR) in this study to present a detailed review of the initial and recent research efforts in Digital video forgery detection, summarizing 260 relevant papers from 2000 to 2023 that have presented a variety of techniques. For analysis, we have presented our references in three different ways: according to the type of forgery detected, according to the type of model or technique used and according to the feature used for forgery detection. We look through the several datasets that are cited in articles and determine their applicable domain. Then, we looked at the numerous measuring metrics employed by different research papers and compared the effectiveness of deep and non-deep models in each category of forgery that was found. Finally, research gaps concerning passive video forgery detection are classified and highlighted. A comparison between our survey and other existing survey articles has been presented in the paper. Researchers who wish to work on video forgery detection will get assistance to determine what kind of efforts in forgery detection work is still required. This survey will also help to select techniques and features based on their
Image inpainting consists of filling holes or missing parts of an image. Inpainting face images with symmetric characteristics is more challenging than inpainting a natural scene. None of the powerful existing models ...
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In the era of digital transformation and increasing concerns regarding data privacy, the concept of Self-Sovereign Identity (SSI) has attained substantial recognization. SSI offers individuals greater control over the...
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Breast cancer is one of the most prevalent cancer types and the second leading cause of death among women. But fortunately, early diagnosis and treatment of breast cancer reduces mortality rates and improves the quali...
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Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and ...
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Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.
Thyroid disorders are increasingly prevalent, making early detection crucial for reducing mortality and complications. Accurate prediction of disease progression and understanding the interplay of clinical features ar...
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Foundation models(FMs) [1] have revolutionized software development and become the core components of large software systems. This paradigm shift, however, demands fundamental re-imagining of software engineering theo...
Foundation models(FMs) [1] have revolutionized software development and become the core components of large software systems. This paradigm shift, however, demands fundamental re-imagining of software engineering theories and methodologies [2]. Instead of replacing existing software modules implemented by symbolic logic, incorporating FMs' capabilities to build software systems requires entirely new modules that leverage the unique capabilities of ***, while FMs excel at handling uncertainty, recognizing patterns, and processing unstructured data, we need new engineering theories that support the paradigm shift from explicitly programming and maintaining user-defined symbolic logic to creating rich, expressive requirements that FMs can accurately perceive and implement.
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